Mitesh P. Patel

Cognitive tactical network models

Unlike commercial MANET applications, tactical networks are typically hierarchical and involve heterogeneous types of radio communications. Future tactical networks also require cognitive functions across the protocol stack to exploit scarce spectrum and dynamically adapt functions and configuration settings. In this work we highlight the need for novel design tools for cognitive tactical networks. We define a system design model that will provide the foundation for generic network design problem formulations via the use of cognitive techniques covering both dynamic frequency adaptations and machinelearning- related aspects of cognition. We use the system model to identify several potential cognitive design knobs and describe how the different design knobs can potentially be adjusted at different timescales of operation. These knobs are used in formulating a cognitive network design problem. Finally, we discuss how a network designer can potentially benefit from the proposed model result, a cognitive network design toolset we have recently developed.

C-NEDAT: A cognitive network engineering design analytic toolset for MANETs

Future force networks of the types envisioned for the network centric warfare (NCW) paradigm will be highly diverse, with the diversity spanning a wide range of (a) requirements (e.g., need for capacity, connectivity, survivability), (b) resources (e.g., radios with widely different capabilities and ‘smart’ (e.g., Software Defined Radios (SDRs)), and (c) environments (e.g., urban, rural). The need to facilitate robust and adaptable communications in such networks has in turn triggered research in the area of cognitive networks that have the ability to ‘learn’ and generate real-time control actions to adapt to the wide diversity of requirements, resources and environments. However, the combination of diversity and “smart” networking exacerbates the problem of generating reliable and robust network designs. We present in this paper, our work on the use of cognitive mechanisms to assist with the design and analysis of robust NCW-like networks. Based on formal network-science based approaches, our Cognitive Network Engineering Design Analytic Toolset (C-NEDAT) provides for a systematic way to design, analyze and maintain robustness of future force MANETs. We provide in this paper an overview of the key functional modules and design capabilities of C-NEDAT and present example results.

Network Layer Congestion Control to Ensure Quality of Service (QoS) in Secure Battlefield Mobile Ad Hoc Networks

To address the quality of service issues in a mobile ad hoc network (MANET) for the diverse set of applications that are carried in the network, the US ARMY CERDEC PILSNER program utilizes a Congestion Control Agent (CCA) as the focal point to facilitate QoS control in a MANET. The main functionalities of CCA include monitoring the traffic loading and queue size status of a router, and based on the measurements, CCA controls the router behavior through dynamically resetting the Weighted Fair Queuing (WFQ) and Random Early Detection (RED) parameters. In this paper, we first describe the main functionalities of CCA, including (1) Dynamically computing the RED parameters¿by measuring the queue size statistics, RED parameters are dynamically adjusted based on the congestion status, such that TCP congestion window is appropriately controlled. (2) Dynamically computing the WFQ parameters¿WFQ parameters are adjusted according to the measured traffic loading for the traffic classes and precedence levels. The underlying algorithm is designed to satisfy the Multi-Level Precedence and Preemption (MLPP) requirement that is unique to military applications. We investigate the performance gain achieved by CCA using OPNET simulation. We show that CCA can manage the MLPP requirements and improve the user-perceived QoS measures like throughput and call success rate.

Realistic wireless emulation for performance evaluation of tactical MANET protocols

Traditional approaches for testing MANET protocols and applications prior to field experimentation often involve simulation tools or small-sized physical testbeds. However, simulation tools typically do not run in real-time and rely on simplified models rather than a real system, while physical testbeds are prohibitively expensive to build and operate. A more practical method is to use emulation tools as they provide high-fidelity network modeling in a cost-effective manner without sacrificing realism. In this paper, we present the use of Wireless IP Scalable EmulatoR (WISER) and its capabilities for testing and evaluating two network routing agents, namely Congestion Control Agent (CCA) and Soft Handoff Agent (SHA), developed for tactical MANETs under the CERDEC PILSNER program. These two agents are integrated within the WISER framework, providing them a scalable and realistic wireless MANET testbed which otherwise was not readily available. Experiments demonstrating interoperability of these technologies are included.

An Integrated Framework for Seamless Soft Handoff in Ad Hoc Networks

We present an integrated architecture for seamless soft handoff in mobile ad hoc networks, where various managers residing on multiple layers are proposed to tackle handoff issues in a cross-layer and cooperative manner. At the link adaptation layer, the virtual interface provides link transparency to the upper layers and session management is handled at the interface manager. At the network layer, most IP-based ad hoc routing protocols can be accommodated. At the transport layer, the transport manager is instructed by the interface manager to adapt the transmission rate according to the new wireless link. Finally, at the application layer, the security manager handles various aspects of security concerns. Simulation results show that our approach can deliver low packet loss, low latency, and smooth handoff solutions with minimum packet overhead. Further, our research on IEEE 802.21 reveals that current media independent handover (MIH) may serve as a component in our integrated architecture. In conclusion, our work represents the first complete solution that provides seamless soft handoff in ad hoc networks with minimum service disruption

Proactive Integrated Link Selection for Network Robustness (PILSNER)

This paper describes a research and development program called Proactive Integrated Link Selection for Network Robustness (PILSNER) that is being executed at the Communications-Electronics Research Development and Engineering Center (CERDEC), Ft. Monmouth, NJ. The objective of PILSNER is to develop, mature and integrate networking technologies that will solve the issues of limited network reliability and connectivity, resulting from the inability to make optimal use of all available link types simultaneously. The PILSNER effort therefore focuses on the development of Pro-active Diverse Link Selection (PAD-LS) technologies, which enable automatic link selection based on network characteristics and mission objectives, over a heterogeneous multi-tiered, multi-link network, in order to bypass congestion and outages. The PAD-LS technologies are designed to proactively allocate and manage bandwidth over multiple transmission paths in order to provide a level of redundancy for assured network availability and connectivity. PAD-LS technologies will address issues related to optimal link selection, capturing link local information and neighbor link information across multi-hop connections, adaptive bandwidth management, IP Quality of Service, IP multicast, and functionality within a mobile tactical environment. Demonstration of these technologies shall be integrated and conducted with a variety of transmission media consistent with the projected Warfighter Information Network - Tactical (WIN-T) capabilities. PILSNER is part of the Tactical Mobile Networks (TMN) Advanced Technology Objective (Demonstration) (ATO(D)), and is scheduled to run from FY2006 through FY2009.

Seamless Soft Handoff in Mobile Ad Hoc Networks

In our MILCOM 2006 paper [1], we have presented an integrated architecture for seamless soft handoff in mobile ad hoc networks, where various managers residing on multiple layers are proposed to tackle handoff issues in a cross-layer and cooperative manner. In this paper, we first demonstrate the handoff performance under nontrivial node mobility. Simulations show that our handoff scheme provides practically equivalent results as the benchmark with no handoff, which indicates that our scheme is quite resistant to node mobility. Next we investigate the general handoff problems where each node can possess multiple radios and nodes are randomly dispersed in some region. In this case, the network topology forms a multi-linked graph (multigraph). By converting the multigraph to simple graphs, our extensive simulations show that our scheme can render low latency, low overhead handoff with minimum packet loss. Finally, we study the synergies with IEEE 802.21 and describe how to integrate IEEE 802.21 into our multi-layer architecture.

Tuning of reinforcement learning parameters applied to OLSR using a cognitive network design tool

In wireless mesh networks, with the standard Optimized Link State Routing (OLSR) metric (i.e. hop count), traffic is routed on the shortest path without considering factors such as traffic distribution and link capacities. Consequently, some nodes may get overloaded from the uneven utilization of network resources. OLSR can be modified to use other link cost metrics, with route selection based on lowest cost path. With delay as the metric, OLSR reduces average round trip time but the load-aware routes may cause wide variance in delay and packet reordering due to route oscillations. We describe a new hybrid routing approach that combines the strength of a) link state routing (e.g. fast convergence), b) load-aware routing (e.g., avoiding congested paths) and c) cognitive routing (e.g. learning to avoid path oscillations). In particular, we investigate the use of Q-learning with OLSR to increase network capacity and reduce congestion delay. We present simulation results for a 36 node dynamic mobile ad hoc network, with standard OLSR, a non-cognitive load-aware OLSR (OLSR-D) and our new hybrid cognitive load-aware OLSR (OLSR-Q). We show that OLSR-Q >; OLSR-D >; OLSR in terms of reducing delay and increasing network capacity. Furthermore, we show that, unlike conventional cognitive Q-routing protocols, our hybrid approach does not reduce performance at low load. Although OLSR-Q can significantly reduce delay and improve capacity, the learning time can reduce connectivity and the distribution of more link state information can reduce raw link capacity. We show how adding OLSR, OLSR-D and OLSR-Q as routing options into the Cognitive Network Engineering Design Analytic Toolset (C-NEDAT), we can select the best routing protocol and parameters (e.g., learning rate) for a given network and its mission. We verify simulation performance improvements by implementing the OLSR-Q in on a 9 node wireless testbed.

TDMA scheduling and channel assignment for cognitive tactical networks

Shortage of spectrum constrains military applications that need to support different classes of traffic. In this work, we study efficient utilization of limited spectrum and propose joint time division multiple access (TDMA) MAC scheduling and channel assignment. First, we formulate the problem as a linear program and propose a centralized algorithm that utilizes the concept of “independent link sets” for scheduling slots and allocating channels. Compared to previous work, our approach supports partial flow loss and allows prioritization of traffic flows. Next, we propose extensions to the distributed USAP MAC protocol (widely used in military applications) to jointly assign TDMA slots and channels to links. Our extensions allow USAP to minimize either slots or channels used in the schedule; a function that is needed for dynamic behavior of future SDR/cognitive radios. We implement our scheduling algorithms in the context of a network design tool (NEDAT) and evaluate their performance using realistic mission scenarios.

Planning & design of routing architectures for multi-tier military networks

Design and planning Military networks requires complex cost-performance trades involving several functions ranging from subnet creation, topology generation, routing hierarchy design & protocol choice, waveform and frequency planning and MAC choices. In this paper we focus on a subset of the design problems pertaining to routing architecture design with unit task organization (UTO) requirements that are critical to military networks. As illustrated in this paper, the choice of routing architecture includes choice of subnets, routing areas and gateways involves complex cost-performance trades. To this end we use a MANET network design toolset Cognitive Network Engineering Design Analytic Toolset (CNEDAT) [1], which is an outcome of a joint project between ACS and US Army CERDEC. CNEDAT is an analytic design tool with a rich set of analytical models for algorithms and protocols for heterogeneous, multi-tier Military Networks. CNEDAT can be used both to: (a) generate/synthesize alternative network designs/plans given a set of network resources, objectives and constraints, by orchestrating various combinations of Waveform, MAC, and network algorithms & protocols, and (b) analyze the resulting network performance to provide options for suitable network stacks and architectures to meet mission objectives. We present in this paper, planning and design of routing architectures that greatly impact network performance and thus play a major decision role while designing and deploying military networks.